WO2009148401A1 - Procédé et appareil associés à la détection de spectre - Google Patents

Procédé et appareil associés à la détection de spectre Download PDF

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Publication number
WO2009148401A1
WO2009148401A1 PCT/SE2009/050673 SE2009050673W WO2009148401A1 WO 2009148401 A1 WO2009148401 A1 WO 2009148401A1 SE 2009050673 W SE2009050673 W SE 2009050673W WO 2009148401 A1 WO2009148401 A1 WO 2009148401A1
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WIPO (PCT)
Prior art keywords
sensors
minimum radius
next minimum
new next
sensor
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PCT/SE2009/050673
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English (en)
Inventor
Yngve SELÉN
Hugo Tullberg
Jonas Kronander
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Telefonaktiebolaget L M Ericsson (Publ)
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Application filed by Telefonaktiebolaget L M Ericsson (Publ) filed Critical Telefonaktiebolaget L M Ericsson (Publ)
Priority to JP2011512415A priority Critical patent/JP5337873B2/ja
Priority to US12/993,555 priority patent/US8270906B2/en
Priority to EP09758628.3A priority patent/EP2283672A4/fr
Publication of WO2009148401A1 publication Critical patent/WO2009148401A1/fr

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/08—Testing, supervising or monitoring using real traffic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/06—Selective distribution of broadcast services, e.g. multimedia broadcast multicast service [MBMS]; Services to user groups; One-way selective calling services
    • H04W4/08—User group management
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W88/00—Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices
    • H04W88/02—Terminal devices

Definitions

  • the present invention pertains to the field of radio communications, and in particular to the part of this field where spectrum utilisation is based on cooperative spectrum sensing.
  • Dynamic Spectrum Access which describes spectrum access where radio units are not limited to using only a specific spectrum band (such as their licensed spectrum) , but rather adapt the spectrum they use depending on conditions such as estimated throughput and latency requirements, spectrum availability etc. For instance, a cellular system suffering from high load in its own licensed spectrum could dynamically access spectral bands owned by some other licensee to temporarily increase its throughput, as long as it does not cause unacceptable interference to the primary system, or a network of communicating nodes may change its operating frequency depending on current spectral conditions. Potentially, dynamic spectrum access can enable more efficient use of the limited resource that radio spectrum is. This is because several systems then share the same resources such that when one system requires only a small amount of spectrum, other systems experiencing higher loads can utilize a greater bandwidth.
  • radio nodes only operate as unlicensed (or secondary) users in a spectral band when triggered to do so.
  • One reason for the radio nodes to initiate communication over unlicensed frequency bands could be that a licensed frequency band (if any) can not fulfill desired needs.
  • Such events may occur, e.g., during peak hours at central stations, during special events such as concerts or sport events, or when several users in the same cell each demand a high bandwidth.
  • the spectrum-on-demand scenario usually looks slightly different depending upon the structure of the network, which may be both centralized and decentralized (autonomous) .
  • a centralized network has a main (or central) node which has a controlling function over the network.
  • centralized networks are the common cellular networks employed today for mobile communication, in which the main node (typically a base station (BS) ) handles all communication with other nodes (user equipments UEs)) within a cell.
  • BS base station
  • Another example of a centralized network is an ad hoc network in which a master node (a function which may be given and handed over to any node in the network) has a regulating function over the other nodes.
  • no node can control the operation of another node
  • Spectrum use is performed according to predetermined rules, or etiquette. If a node experiences an increased bandwidth demand, it can increase its use of a shared spectrum, if neighbouring nodes accept this, e.g., if they are willing to reduce their spectrum use.
  • the node can try to detect and access spectrum unused by the system (which does not necessarily have to be shared with the other nodes) to meet the demand.
  • Sensing is the act of determining, by monitoring radio transmissions, whether e.g. a particular spectrum band is currently at least in part free for use. That is, sensing is a way of finding spectrum opportunities, which may be accessed in a dynamic, and possibly secondary, manner.
  • a device which takes part in the sensing is usually referred to as a sensor.
  • Various network nodes such as user equipments and base stations, may act as sensors. Since spectrum opportunities which are identified by sensing can be viewed as less reliable than spectrum specifically licensed for the system, these opportunities may, e.g., be used for transmissions that are considered to be non time-critical.
  • a sensor performing spectrum sensing will deplete overall system resources. For example, the sensor will use power for its receiver and baseband circuitry and may thus reduce a battery life-time, and the sensing process will consume processing capacity. Also, a sensor normally needs to report its sensing result somehow, which requires additional communication resources. It is therefore desirable to use few sensors in the sensing, while still having a sufficient number such that the sensing is reliable. In this sense, the number of sensors to use is a trade-off between having a high reliability of the sensing result, and having a low or reasonable demand on resources, such as battery capacity of the partaking sensors, and transmission overhead in the communication system. Consequently, there exists a need to be able to select the sensors that participate in the cooperate sensing in an "optimal" manner which suitably balances these conflicting aspects.
  • One object of the present invention is therefore to overcome or at least mitigate at least one of the above-indicated difficulties .
  • the above- stated object is achieved with a method according to the following.
  • a candidate set of sensors that are available to participate in an occasion of cooperative spectrum sensing is obtained.
  • For each sensor in the candidate set its radial distance to a central coordinating node in a communication system is also obtained.
  • a sequence of minimum radii is produced.
  • the number of sensors that can be accommodated at that radius is determined. That is, this number is the greatest number of sensors that can be placed on circle having this radius without a probability that all these sensors are mutually uncorrelated falling below a first design probability threshold.
  • the first minimum radius is set to zero, and the corresponding number of sensors that can be accommodated at this minimum radius is set to one.
  • the central coordinating node is selected to an active set of sensors that are to participate in the cooperative spectrum sensing.
  • Each one of the other minimum radii is calculated based on the previous minimum radius in the sequence and the number of sensors that can be accommodated at this previous minimum radius. This is done by calculating the minimum radius such that an estimated probability of a sensor at this minimum radius being correlated with any sensor that could be accommodated at the previous minimum radius in the sequence is equal to a second design probability threshold.
  • a calculated minimum radius is also checked against one or more constraints. If the calculated minimum radius does not fulfil the one or more constraints, the minimum radius is recalculated such that the one or more constraints are fulfilled.
  • Sensors are now selected to the active set from the candidate set based on the sequence of minimum radii and the corresponding accommodation numbers.
  • the candidate set includes a number, which is equal to or greater than the number of sensors that can be accommodated at that particular minimum radius, of sensors which all have radial distances to the central coordinating node that exceed this particular minimum radius, then a number, equal to the number of sensors that can be accommodated at this minimum radius, of sensors which have the smallest radial distances to the central coordinating node that still exceed the particular minimum radius are selected from the candidate set to the active set.
  • the above- stated object is achieved with an element for sensors selection which is configured to perform the above method.
  • One advantage with embodiments of the present invention is that efficient and systematic approaches to sensor selection for cooperative spectrum sensing are provided. By not necessarily involving every candidate sensor in cooperate spectrum sensing, a strain on system resources introduced by cooperate spectrum sensing can be kept at an acceptably low level. Furthermore, the systematic selection of sensors to the active set suggested above, assures that cooperate sensing still becomes fairly reliable . Another advantage is that embodiments of the invention only need to use radial distances to the central coordinating node, rather than more complete positioning information. Such radial distances are fairly easy to obtain in most systems. Using radial distance information, it is of course possible to identify sensors which are guaranteed to be uncorrelated, i.e. the distances between sensors are greater than a predetermined decorrelation distance.
  • Figure 1 is a schematic network diagram illustrating an exemplary spectrum-on-demand situation where embodiments of the invention may be applied.
  • Figure 2 is a frequency-time diagram illustrating spectrum-on- demand operation in the network situation illustrated in figure 1.
  • Figure 3 is a flow chart illustrating a cooperative spectrum sensing operation according to an embodiment of the invention.
  • Figure 4 is a block diagram illustrating an apparatus with an element for sensor selection according to an embodiment of the invention .
  • Figure 5 is a block diagram illustrating an apparatus connected to an element for sensor selection according to an embodiment of the invention.
  • Figure 6 is a geometric diagram.
  • Figure 7 is a flow chart illustrating a method according to an embodiment of the invention.
  • Figure 8 is a block diagram illustrating an element for sensor selection according to an implementation embodiment of the invention .
  • FIG. 1 is schematic network diagram illustrating one, purely exemplary, spectrum-on-demand situation where embodiments of the present invention may be applied.
  • the system Sl is a television broadcasting system, symbolically represented by two broadcasting antennas Pl and P2 ; and the system S2 is a cellular radio communication system, symbolically represented by two base stations BSl and BS2, which provide radio coverage in cells Cl and C2, respectively.
  • a number of user equipments (UE) serviced by the system S2 are also shown.
  • the system Sl has a license for a spectrum band Bl.
  • the system S2 which has a license to another spectrum band B2, also wants to be able to exploit spectrum opportunities in the spectrum band Bl. Consequently, the system S2 thus has a reliable spectrum band B2 in which it can schedule control signalling as well as data and other forms of communication. At the same time, if required or desired, it has the option to temporarily extend its available spectrum by using the less reliable spectrum band Bl as a secondary user. As long as a system load in the system S2 is low relative to the bandwidth of the spectrum band B2, it is probably not necessary for the system S2 to use resources in the spectrum band Bl.
  • the system S2 needs to develop an awareness of the spectrum opportunities existing in the spectrum band Bl, that is, radio resources (e.g. time/frequency resources or codes) in the spectrum band Bl which are currently not used by the system Sl, or by any other system operating as secondary user in the spectrum band Bl.
  • radio resources e.g. time/frequency resources or codes
  • the system Sl does not directly supply the system S2 with information on spectrum opportunities in the spectrum band Bl .
  • the system S2 therefore has to detect the opportunities itself by means of sensing. If the system S2, after having performed sensing, is confident that there are resources in the spectrum band Bl which are not being used, the system S2 may choose to use those resources for its own traffic.
  • Figure 2 is a frequency-time diagram that provides an example of spectrum-on-demand operation applied to the network situation of figure 1.
  • the system S2 experiences an increased spectrum demand when its licensed spectrum band Bl becomes fully utilized.
  • the system S2 starts to sense the band Bl in search for spectrum opportunities.
  • system S2 has detected a spectrum opportunity and starts to use part of the spectrum band Bl in a secondary manner.
  • the spectrum demand in the system S2 decreases but S2 still utilizes resources in Bl.
  • the spectrum demand decreases further and the system S2 abandons the spectrum band Bl .
  • the sensing in the system S2 is preferably performed in a cooperative manner involving a plurality of sensors, in order to improve the sensing reliability.
  • the nodes of the system S2, such as base stations and/or serviced user equipments, may act sensors .
  • Figure 3 is a flow chart that illustrates one example of cooperative sensing in accordance with an embodiment of the invention.
  • the left side of figure 3 illustrates actions performed in a base station, which here act as an initiating and coordinating node for the cooperative spectrum sensing.
  • the right side of figure 3 illustrates actions performed in one exemplary sensor.
  • the base station determines that more spectrum is needed in order to support the communication demand.
  • the base station maintains a list of sensors that can be seen as candidates for participation in cooperative sensing. This list thus contains a candidate set of sensors.
  • Such a candidate set is a subset of a "total set", that is, all nodes in some geographical area.
  • the total set can be all nodes associated with that central node.
  • Reasons why a particular node is not a member of the candidate set are permanent factors, e.g., the node may lack the necessary functionalities, such as support of the spectrum band to be sensed, and/or temporary factors, e.g., the battery level of the node is too low to participate.
  • the base station determines, at a block 13, whether the list is up to date.
  • the base station sends a sense request to all nodes associated the base station at a block 15. This sense request is then received by the sensors, illustrated by the exemplary sensor at a block 17.
  • the exemplary sensor processes the sense request at a block 19 to determine whether it is currently a candidate for participation in cooperative spectrum sensing. In this particular example, it is assumed that the exemplary sensor is a candidate for cooperative spectrum sensing, and this fact is communicated to the base station in a response at a block 21.
  • the base station receives this response, and possibly similar responses from other nodes, at a block 25. Based on the received responses, the base station updates the sensor list at a block 27.
  • the base stations partitions the candidate set into two sets, one active set and one passive set.
  • the active set contains the sensors that will participate in the cooperative sensing at this particular time
  • the passive set contains the sensors in the candidate set that will not participate in the cooperative sensing at this particular time. It, of course, suffices to determine one of these sets, e.g. the active set. The other set is then implicitly determined as well.
  • the base station sends, at a block 31, a sense order that orders all sensors in the active set to perform sensing. In this example it is assumed that the exemplary sensor is in the active set, and the exemplary sensor receives the sense order at a block 33.
  • the exemplary sensor performs sensing at a block 35. After the sensing has been performed, the exemplary sensor sends a result of the sensing in a sense report to the base station at a block 37. After a timeout 39 (i.e., a waiting period), the base station receives this sense report, and similar sense reports from other sensors in the active set, at a block 41, and the received sense reports are then processed by the base station at a block 43. The processing of the sense reports results in a spectrum decision at a block 45. The spectrum decision establishes whether or not one or more spectrum opportunities have been detected as a result of the cooperative spectrum sensing.
  • the base station transmits the spectrum decision and possibly additional information to relevant system nodes (e.g., nodes which are scheduled for transmission or reception in the detected spectrum opportunities) .
  • relevant system nodes e.g., nodes which are scheduled for transmission or reception in the detected spectrum opportunities.
  • the exemplary node receives this transmission at a block 49.
  • the partitioning of the candidate set into the active set and the passive set is allowed vary over time.
  • the base station is responsible for partitioning the candidate set into the active set and the passive set, thereby in effect determining the sensors that should participate in the cooperative sensing.
  • any apparatus not necessarily a base station, which has access to an element for sensor selection can be made responsible for this partitioning of the candidate set.
  • Figure 4 is a schematic block diagram illustrating one example of such an apparatus 51.
  • an element for sensor selection 53 is provided and contained in apparatus 51.
  • a similar block diagram is shown in figure 5.
  • the element for sensor selection 53 and the apparatus 51 are physically distinct units that communicate through a communication channel 55.
  • the element for sensor selection 53 can be implemented in various ways employing standard circuit technologies, such as application specific circuitry, programmable circuitry, or any combination thereof.
  • the element 53 may also fully or partly be implemented with one or more processors programmed with suitable software.
  • the element for sensor selection can also be a single unit, or the sensor selection functionality can be distributed over several units, e.g., several processors in a device, or several communicating devices .
  • Figure 8 is block diagram that illustrates a particular implementation embodiment of the element for sensor selection 53.
  • the element for sensor selection 53 comprises a processor 151, a memory unit 153, and an input-output unit 155, which are all operationally connected, e.g. by means of a digital bus 157.
  • the memory unit 153 stores a database 159 with information relevant to the selection process.
  • the database 159 includes information, which may initially have been received via the input-output unit 155, identifying the candidate set and other information relating to the candidate set, such as, for example, positioning information.
  • the database 159 may also contain pre-stored data that can be used in the selection process, as will be exemplified below.
  • the processor performs the selection process using software 161 and data that are provided by the memory unit 153 or via the input-output unit 155. A result of the selection process may be communicated via the input-output unit 155.
  • the element for sensor selection 53 may in particular be configured to perform any one of the methods described and indicated below.
  • Shadow fading arises from propagation loss behind large structures such as buildings and mountains.
  • the shadowing is spatially correlated and one model of the correlation, which is a function of distance d between two terminals, R(d), is
  • a is an environment parameter.
  • the propagation environment can be characterized by a decorrelation distance, do, which is a minimum separation between sensors required for a shadowing correlation to fall below a pre-determined threshold.
  • This threshold can be selected as a user parameter. Essentially, it represents a tradeoff between the amount of sensors selectable, if "uncorrelated" sensors are desired, and the correlation level of the selected sensors.
  • the decorrelation distance do can be obtained from the equation above, for a given correlation threshold. In the following we will use the term uncorrelated shadowing for shadowing correlation below the threshold, i.e., when the separation of the two sensors is larger than do. The sensors are then said to be "uncorrelated”, otherwise the sensors are said to be "correlated”.
  • radius information i.e., the distances from the coordinating node to the other available sensors in the candidate set.
  • This distance information can be obtained from propagation times, timing advance, or similar features. Strictly speaking, this gives the distances the electromagnetic waves have travelled, rather than the physical distances. However, the differences are usually small and it is not unlikely that insufficient timing resolution in a receiver will cause larger errors than the difference between physical distance and propagation distance.
  • FIG. 6 is a geometric diagram that illustrates this situation.
  • a central coordinating node such as a base station, master node or similar, is here located at a point 61, and two circles 63 and 65 centred at the point 61 are drawn.
  • the circles 63 and 65 have radii rl and r2, respectively.
  • rl is greater than r2.
  • the formulas that will be presented apply also when r2 is equal to or greater than rl .
  • One sensor is assumed to be located on the circle 63 at an arbitrary point 67.
  • a third circle 69 centred at the point 67 and having a radius dO, is drawn.
  • any sensor located on or within the circle 69 will be correlated with the sensor at the point 67, and when a restriction is made to the circle 65, this means any sensor on an indicated circle segment 70.
  • the law of cosines it can be shown that a length s of the circle segment 70 is
  • a probability that the sensor at the point 67 is correlated with a particular sensor on the circle 65 is simply a ratio between the length s of the circle segment 70 and a total length of the circle 65, that is,
  • Equation (2.1a) is clearly only an approximation.
  • the right hand side is in fact an upper bound to the left hand side.
  • An "exact” equation can, of course, be obtained by using a standard ⁇ inclusion-and-exclusion-formula" (and assuming statistically independent sensor locations on the circle 65)
  • a cell of the central coordinating node may be divided into N sectors, where N denotes an integer that is greater than one.
  • N denotes an integer that is greater than one.
  • correlation with sensors outside of the sector where a particular sensor is located is not considered.
  • the number of sensors that can be "accommodated" at or approximately equal radius rl from the central coordinating node is here taken to mean the largest integer K such that P[K uncorrelated sensors] >T (using either one of (3a) or (3b) depending on the cell case) , where T is a first design probability threshold.
  • the candidate set is partitioned into an active and a passive set based on actual radii to the sensors relative to the central coordinating node.
  • the method takes as its input the candidate set of sensors, where the distances (radii) from the central coordinating node to each candidate sensor is known. Another input to the method is the first design probability threshold T and possibly a second design probability of threshold D (see below) .
  • the variable k is here used as a variable that indicates the number of sensor that can be accommodated at the next minimum radius, the variable k thus indicates an "accommodation number".
  • a new next minimum radius will subsequently be calculated, and k will then be updated to indicate the number sensors that can be accommodated at the new next minimum radius.
  • the central coordinating node (BS or master node in an ad hoc network) is then selected as the first node in the active set.
  • a new next minimum radius r' is computed by setting P[corr(k)] (using either (2a) and (2.1a) or
  • the second design probability threshold D may be equal to the first design probability threshold T, i.e. only one threshold is used.
  • the value r' is now checked against one or more constraints.
  • One example of such a constraint is a minimum increase in radius between r and r' , r' ⁇ r+c, where c can be related to the decorrelation distance dO .
  • Another example of a constraint is that for certain values of the second design probability threshold D, radius r, and decorrelation distance d ⁇ , there exist no real solutions for rl to equations (2.1a) or (2.1b), in which case some parameter, for example, the second design probability threshold D, must be adjusted such that a solution exists.
  • An alternative, however, is to replace equality with an inequality, e.g. to require, instead, that P[corr(k)] ⁇ D, then a solution can always be found, and preferably a value of rl which is as small as possible, but still fulfilling the inequality, should be selected.
  • the method sets r equal to r' .
  • the method proceeds to selecting the k sensors with smallest radii still greater than r, if k such sensors exist. If k such sensors exist they are selected to the active set and the method returns to the steps of updating r and k as described above.
  • This method may optionally terminate when a specified desired value of active sensors has been reached. If no such value is specified then the method below runs without modification. Another option is to run the method without limitation on the number of active sensors and, after termination of the method, if the number of sensors in the active set exceeds the desired value, purge the active set, e.g. by removing the sensor (s) with the smallest radial difference (s) . If it is desirable from a speed and complexity standpoint we can pre-compute the next minimum radius r' given r and the number of sensors k that can be accommodated at r, given the threshold D.
  • Figure 7 is a flow chart that illustrates a method of sensor selection according to an implementation embodiment of the invention.
  • an input to the method is provided at a block 73.
  • the input includes the candidate set of sensors with associated sensor radii relative to the central coordinating node, here a base station, and the design probability thresholds T and D, or one of these thresholds in an embodiment where they are considered equal.
  • the variable r is set to 0 and the variable k is set to 1.
  • the base station is then selected to the active set at a block 77.
  • the new next minimum radius r' is computed, in the manner explained above.
  • a block 89 it is checked whether the candidate set contains k sensors with radii to the central coordinating node which are greater than r. If this is the case, the k sensors with smallest radii still greater than r are picked from the candidate set to the active set. Thereafter, the method returns to the block 79, and the method is repeated as described. If, however, there does not exist k sensors with radii greater than r, then any sensors with radii greater than r are added to the active set by virtue of blocks 93 and 95, and the method ends at a block 97.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)
  • Monitoring And Testing Of Transmission In General (AREA)

Abstract

L'invention concerne un procédé et un appareil correspondant (53). Un ensemble candidat de capteurs qui sont disponibles pour participer à une occasion de détection de spectre coopérative est obtenu. Pour chaque capteur dans l'ensemble candidat, sa distance radiale jusqu'à un noeud de coordination central dans un système de communication est également obtenue (73). Une séquence de rayons minimum est produite (75,79). Pour chaque rayon minimum dans la séquence, un nombre d'adaptation est déterminé (75,87). Le nombre d'adaptation associé à un rayon minimum est le plus grand nombre de capteurs pouvant être placés sur le cercle présentant ledit rayon sans la probabilité que tous les capteurs ne soient mutuellement corrélés, la corrélation passant sous un seuil de probabilité de conception. Des capteurs de l'ensemble candidat sont alors sélectivement ajoutés (91, 95) à un ensemble actif de capteurs sur la base des rayons minimum, des nombres d'adaptation correspondants et des distances radiales obtenues.
PCT/SE2009/050673 2008-06-04 2009-06-04 Procédé et appareil associés à la détection de spectre WO2009148401A1 (fr)

Priority Applications (3)

Application Number Priority Date Filing Date Title
JP2011512415A JP5337873B2 (ja) 2008-06-04 2009-06-04 スペクトラムセンシングに関する方法と装置
US12/993,555 US8270906B2 (en) 2008-06-04 2009-06-04 Method and apparatus relating to spectrum sensing
EP09758628.3A EP2283672A4 (fr) 2008-06-04 2009-06-04 Procédé et appareil associés à la détection de spectre

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US5866808P 2008-06-04 2008-06-04
US61/058,668 2008-06-04

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CN102057736A (zh) 2011-05-11
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WO2009148393A1 (fr) 2009-12-10
EP2283671A4 (fr) 2017-06-28
JP5337873B2 (ja) 2013-11-06
US8509701B2 (en) 2013-08-13
EP2283685B1 (fr) 2019-08-07
EP2283685A1 (fr) 2011-02-16
EP2283672A1 (fr) 2011-02-16
CN102057736B (zh) 2014-04-09
EP2283671B1 (fr) 2019-08-07
WO2009148399A1 (fr) 2009-12-10
US8270906B2 (en) 2012-09-18
CN102057711A (zh) 2011-05-11
US20110098005A1 (en) 2011-04-28
JP2011524126A (ja) 2011-08-25
CN102057711B (zh) 2013-09-25
EP2283672A4 (fr) 2017-03-22
HUE047383T2 (hu) 2020-04-28
PL2283685T3 (pl) 2020-03-31
US20110076959A1 (en) 2011-03-31
ES2751718T3 (es) 2020-04-01
US20110065471A1 (en) 2011-03-17
US8995922B2 (en) 2015-03-31

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